KECIR at the NTCIR-10 INTENT Task

This paper describes the approaches and results of our system for the NTCIR-10 INTENT task. We present some methods for Subtopic Mining subtask and Document Ranking subtask. In the Subtopic Mining subtask, we employ a voting method to rank candidate subtopics and semantic resource HowNet was used to merge those candidate subtopics which may impact diversity. In the Document Ranking Subtask, we also employ a voting method based on the mined subtopics. In the Chinese subtopic mining, our best values of I − rec@10, D − nDCG@10 and D# − nDCG@10 were separately 0.3743, 0.3965 and 0.3854. In the Document Ranking subtask, they were separately 0.6366, 0.3998 and 0.5182.